The COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system

Background: Appendectomy is still one of the most commonly performed emergency surgical procedures worldwide.Avoiding delays in the diagnosis in these patients may play a role in reducing observed morbidity.Aim of study:To analyze the clinico-pathological profile and outcomes of patients undergoing emergency appendectomies to determine risk factors influencingcomplicaions.Type of the study: A prospective analytic studyPatients and Methods: The study involves 108 patients underwent emergency appendectomies at Al-kindy teaching hospital from April 2014 to March 2015. Appendicitis was categorized into two groups perforated andnonperforatedappendicities. A comparison between them was made in regard to Gender, Age, clinical presentation, inve

To find out the impact of maternal risk factors on the outcome of pregnancy in Baghdad city. A descriptive purposive study was carried out on 100 postpartum women who had delivered for 1 hr. to 24 hrs. ago . the study sample was selected from three hospitals in Baghdad city ( Baghdad teaching hospital ,Fatima Al-Zahra'a maternity and pediatric teaching hospital and Al-Yarmook teaching hospital),during the period from 25 Jan. to 25 Feb. 2006. The data were collected through the use of questionnaire format reviewing pregnants' records and personal interview and were analyzed by using descriptive and inferential statistical approaches. The finding revealed that maternal pregnancy complications had weak effects on pregnancy outcome , while mate

The COVID-19 pandemic has had a huge influence on human lives all around the world. The virus spread quickly and impacted millions of individuals, resulting in a large number of hospitalizations and fatalities. The pandemic has also impacted economics, education, and social connections, among other aspects of life. Coronavirus-generated Computed Tomography (CT) scans have Regions of Interest (ROIs). The use of a modified U-Net model structure to categorize the region of interest at the pixel level is a promising strategy that may increase the accuracy of detecting COVID-19-associated anomalies in CT images. The suggested method seeks to detect and isolate ROIs in CT scans that show the existence of ground-glass opacity, which is fre

Objective: to assess the risk factors of coronary artery disease patients.
Methodology: A non-probability (purposive) sample of (100) patients. The study population consisted of
a sample of adults from both genders whose ages were 30 years and more, and was newly diagnosed as
having CAD by coronary angiography in the cardiac catheterization unit of An Nasiriyah heart center.
Results: The result of the study showed that the most common modifiable risk factors were low HDL-C
levels (58%), smoking (53%), hypertension (46%), diabetes mellitus (34%), obesity (30%), high
triglycerides (19%), hypercholesterolemia (17%), and high LDLC (14%). All these factors were positively
and significantly associated with the development